Lifeboat Foundation

Building a useful quantum computer in practice is incredibly challenging. Significant improvements are needed in the scale, fidelity, speed, reliability, and programmability of quantum computers to fully realize their benefits. Powerful tools are needed to help with the many complex physics and engineering challenges that stand in the way of useful quantum computing.

AI is fundamentally transforming the landscape of technology, reshaping industries, and altering how we interact with the digital world. The ability to take data and generate intelligence paves the way for groundbreaking solutions to some of the most challenging problems facing society today. From personalized medicine to autonomous vehicles, AI is at the forefront of a technological revolution that promises to redefine the future, including many challenging problems standing in the way of useful quantum computing.

Quantum computers will integrate with conventional supercomputers and accelerate key parts of challenging problems relevant to government, academia, and industry. This relationship is described in An Introduction to Quantum Accelerated Supercomputing. The advantages of integrating quantum computers with supercomputers are reciprocal, and this tight integration will also enable AI to help solve the most important challenges standing in the way of useful quantum computing.

(TNS) — The global race for computational power is well underway, fueled by a worldwide boom in artificial intelligence. OpenAI’s Sam Altman is seeking to raise as much as $7 trillion for a chipmaking venture. Tech giants like Microsoft and Amazon are building AI chips of their own. The need for more computing horsepower to train and use AI models—fueling a quest for everything from cutting-edge chips to giant data sets—isn’t just a current source of geopolitical leverage (as with US curbs on chip exports to China). It is also shaping the way nations will grow and compete in the future, with governments from India to the UK developing national strategies and stockpiling Nvidia graphics processing units.

I believe it’s high time for America to have its own national compute strategy: an Apollo program for the age of AI.

In January, under President Biden’s executive order on AI, the National Science Foundation launched a pilot program for the National AI Research Resource (NAIRR), envisioned as a “shared research infrastructure” to provide AI computing power, access to open government and nongovernment data sets, and training resources to students and AI researchers.

U.S. government warns of North Korean hackers sending spoofed emails to gather intelligence.

Buyer is responsible for relocation of 26,000 pounds of equipment.

A Chinese company says it’s successfully developed a brain chip and implanted it into a monkey — who can now remotely control a robot arm with the device.

That’s according to state-run news media outfit Xinhua, putting Elon Musk’s startup Neuralink on notice that there will be international as well as domestic competition for his brain-computer interface venture.

The company, Beijing Xinzhida Neurotechnology, which is backed by the Chinese government, unveiled its device, the NeuCyber Array BMI (brain-machine interface) System at a technology convention in Beijing on Thursday, according to Reuters.

Read how Congress is pressing the DEA to reclassify marijuana from a Schedule I drug to Schedule III.

Marijuana is currently classified as a Schedule I drug, meaning these are “drugs with no currently accepted medical use and a high potential for abuse.” However, a team of 21 bipartisan congressional leaders from both the Senate and House of Representatives hopes to change that as they recently sent a letter to the United States Drug Enforcement Administration (DEA) pushing them to “promptly remove marijuana from Schedule I of the Controlled Substances Act (CSA)”, noting that almost eight months had passed “since the Department of Health and Human Services (HHS) recommended rescheduling marijuana to Schedule III — and 18 months since President Biden directed HHS and the Department of Justice (DOJ) to begin the process of reviewing marijuana’s scheduling.”

Examples of other Schedule I drugs include heroin, lysergic acid diethylamide (LSD), marijuana (cannabis), 3,4-methylenedioxymethamphetamine (ecstasy), methaqualone, and peyote, while Schedule III drugs include Tylenol, ketamine, anabolic steroids, and testosterone. Additionally, the penalties between Schedule I and Schedule III drugs also demonstrate stark contrasts, as well.

Continue reading “Bipartisan Effort Demands DEA Action on Marijuana Scheduling” »

Science And Technology For Emerging National Security Threats — Dr. Sean Kirkpatrick, Ph.D. — Nonlinear Solutions LLC — Fmr. Director, All-domain Anomaly Resolution Office (AARO), United States Department of Defense.

Dr. Sean Kirkpatrick, Ph.D. is Owner of Nonlinear Solutions LLC., an advisory group that provides strategic scientific and intelligence consulting services, with a focus on emerging science and technology trends, to clients in both the defense and intelligence communities.

Continue reading “Dr. Sean Kirkpatrick, Ph.D. — Science And Technology For Emerging National Security Threats” »

Jason Matheny is a delight to speak with, provided you’re up for a lengthy conversation about potential technological and biomedical catastrophe.

Now CEO and president of Rand Corporation, Matheny has built a career out of thinking about such gloomy scenarios. An economist by training with a focus on public health, he dived into the worlds of pharmaceutical development and cultivated meat before turning his attention to national security.

As director of Intelligence Advanced Research Projects Activity, the US intelligence community’s research agency, he pushed for more attention to the dangers of biological weapons and badly designed artificial intelligence. In 2021, Matheny was tapped to be President Biden’s senior adviser on technology and national security issues. And then, in July of last year, he became CEO and president of Rand, the oldest nonprofit think tank in the US, which has shaped government policy on nuclear strategy, the Vietnam War, and the development of the internet.

Indeed, the costs of building fabs in Germany, Japan, and the U.S. are higher than the costs of building fabs in Taiwan and TSMC has complained about it a number of times in the past. The company even had to delay production start at its Fab 21 near Phoenix, Arizona, due to problems with tools installation and negotiations with trade unions.

Therefore, if a TSMC customer wants to produce its chips at a specific location, then the foundry will charge a premium. How high is that premium will be remains to be seen, but last year a media report indicated that chips made in Arizona on TSMC’s N5 and N4 production nodes could be from 20% to 30% more expensive than the same chips produced in Taiwan.

Due to higher construction and operational expenses of fabs in Japan, Germany, and the U.S., TSMC plans to transfer these additional costs to its customers to sustain its target gross margin of 53%. Although American chip designers may not welcome the increased production costs in the U.S., they will probably manufacture chips intended for government and other markets less sensitive to price increases at the Arizona facility. Consequently, they should manage to pass on these higher costs to at least some of their end customers without jeopardizing their market competitiveness.